The present invention relates to the field of cardiovascular disease. More specifically, it relates to a diagnostic test which can be used to determine whether an individual or test subject is at a lower risk or higher risk of developing or having cardiovascular disease than other individuals in a given population of human subjects.
Cardiovascular disease (CVD) is the general term for heart and blood vessel diseases, including atherosclerosis, coronary heart disease, cerebrovascular disease, and peripheral vascular disease. Cardiovascular disorders are acute manifestations of CVD and include myocardial infarction, stroke, angina pectoris, transient ischemic attacks, and congestive heart failure. CVD accounts for one in every two deaths in the United States and is the number one killer disease. Thus, prevention of cardiovascular disease is an area of major public health importance.
A low fat diet and exercise are recommended to prevent CVD. In addition, a number of drugs may be prescribed by medical professionals to those persons who are known to be at risk for developing CVD. These include lipid lowering agents which reduce blood levels of cholesterol and triglycerides. Medications to normalize blood pressure are used in hypertensive patients. Medications which prevent activation of platelets, such as aspirin, may also be prescribed for patients at risk for developing CVD. More aggressive therapy, such as administration of multiple medications, may be used in those individuals who are at high risk. Since CVD therapies may have adverse side effects, it is desirable to have diagnostic tests for identifying those individuals who are at risk, particularly those individuals who are at high risk, of developing CVD.
Currently, several risk factors are used by members of the medical profession to assess an individual's risk of developing CVD and to identify individuals at high risk. Major risk factors for cardiovascular disease include hypertension, family history of premature CVD, smoking, high total cholesterol, low HDL cholesterol, and diabetes. The major risk factors for CVD are additive, and are typically used together by physicians in a risk prediction algorithm to target those individuals who are most likely to benefit from treatment for CVD. These algorithms achieve a high sensitivity and specificity for predicting 15% risk of CVD within 10 years. However, the ability of the present algorithms to predict a higher probability of developing CVD is limited. Among those individuals with none of the current risk factors, the 10-year risk for developing CVD is still about 2%. In addition, a large number of cardiovascular disorders occur in individuals with apparently low to moderate risk profiles, as determined using currently known risk factors. Thus, there is a need to expand the present cardiovascular risk algorithm to identify a larger spectrum of individuals at risk for or affected with CVD.
The mechanism of atherosclerosis is not well understood. Over the past decade a wealth of clinical, pathological, biochemical and genetic data support the notion that atherosclerosis is a chronic inflammatory disorder. Acute phase reactants (e.g., C-reactive protein, complement proteins), sensitive but non-specific markers of inflammation, are enriched in fatty streaks and later stages of atherosclerotic lesions. In a recent prospective clinical trial, base-line plasma levels of C-reactive protein independently predicted risk of first-time myocardial infarction and stroke in apparently healthy individuals. U.S. Pat. No. 6,040,147 describes methods which use C-reactive protein, cytokines, and cellular adhesion molecules to characterize an individual's risk of developing a cardiovascular disorder. Although useful, these markers may be found in the blood of individuals with inflammation due to causes other than CVD, and thus, these markers are not highly specific.
Accordingly, the need still exits for additional diagnostic tests for characterizing an individuals risk of developing or of having cardiovascular disease. Diagnostic tests which employ risk factors that are independent of traditional CVD risk factors such as LDL levels are especially desirable.